Hybrid cooling control of a computing system

ABSTRACT

In one implementation, a system for hybrid cooling control of a computing system includes a coordinated controller engine to: determine a number of liquid loop set-points and a number of air loop set-points, determine a number of system parameters corresponding to the number of liquid loop set-points and the number of air loop set-points, determine a correlation factor for the number of system parameters; and alter the number of liquid loop set-points and the number of air loop set-points based on the correlation factor to lower an energy consumption or to maximize energy reuse of a number of cooling resources associated with the number of system parameters.

BACKGROUND

Computing systems (e.g., data centers, server racks, computing hardware,etc.) can utilize a number of methods for cooling to maintain atemperature of the computing hardware within the computing system. Thecooling methods can utilize set-points to maintain correspondingtemperatures for hardware within the computing systems. The set-pointscan be utilized to activate and/or deactivate a cooling method when amonitored temperature reaches the set-point. The cooling methods can beseparated into a number of control loops (e.g., cooling distributionunit (CDU) loop, rack water loop, rack air loop, etc.) that operateindependently.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a diagram of an example of a system for hybridcooling control of a computing system consistent with the presentdisclosure.

FIG. 2 illustrates a diagram of an example computing device consistentwith the present disclosure.

FIG. 3 illustrates a diagram of an example of a system for hybridcooling control of a computing system consistent with the presentdisclosure.

FIG. 4 illustrates a diagram of an example of a system for hybridcooling control of a computing system consistent with the presentdisclosure.

FIG. 5 illustrates a diagram of an example of a system for hybridcooling control of a computing system consistent with the presentdisclosure.

FIG. 6 illustrates a diagram of an example of a system for hybridcooling control of a computing system consistent with the presentdisclosure.

DETAILED DESCRIPTION

A number of methods, systems, and computer readable medium for hybridcooling control of a computing system are described herein. The hybridcooling control of a computing system can include a number of individualcooling loops (e.g., liquid cooling loop, air cooling loop, etc.) tomaintain a temperature of the computing system. For example, the hybridcooling control system can include a liquid loop that can include anumber of cooling distribution units (CDUs) that are coupled to a numberof heat exchangers (HEX) and/or component water cooling loops (e.g., ITwater cooling loops (ITWCL)). In addition, the hybrid cooling controlsystem can include an air loop that can include a number of heatexchanger fans, rack fans, and/or server fans to circulate air withinthe computing system. The hybrid cooling control system can utilize theliquid loop and the air loop simultaneously to maintain a temperature ofhardware within the computing system.

Previous cooling systems for computing systems can operate a liquid loopand an air loop independently. Operating the liquid loop and air loopindependently can result in inefficient energy utilization, powerutilization (e.g., maximum power utilization, etc.), and/or wastingcooling capacity (e.g., excessive cooling resource usage, etc.). Forexample, previous cooling systems can increase a cooling capacity of theliquid loop and/or the air loop without considering the energyconsumption or a correlation factor between the set-points of the liquidloop and air loop. As used herein, the correlation factor (e.g.,sensitivity functions, input changes and corresponding output changes)can be a value that represents how a set-point of the liquid loop or airloop affects the performance metrics of the cooling system and/or anenergy consumption or energy reuse of the cooling system. The set-pointscan be settings that indicate when a cooling resource is activatedand/or deactivated. For example, the set-points of the liquid loop caninclude a set-point that indicates a temperature at which a pump speedis to be increased. In another example, the set-points can be comparedto real-time measurements (e.g., real-time component return watertemperature, server component temperatures, etc.) and the coolingresources (e.g., cooling devices associated with cooling loops, etc.)can be activated, deactivated, and/or altered based on the comparisonbetween the set-points and the real-time measurements.

The set-points can be utilized in a number of control loops. The controlloops can be utilized to compare the set-points to the real-timemeasurements. In some examples, there can be a first control loop for aliquid loop and a second control loop for an air loop. That is, aphysical liquid cooling loop can include a first control loop that canbe utilized to compare liquid loop set-points to real-time measurements(e.g., component supply water temperatures, server componenttemperatures, etc.) and a physical air cooling loop can include a secondcontrol loop that can be utilized to compare air loop set-points toreal-time measurements (e.g., inlet air temperature, server air pressuredrop, etc.).

The hybrid cooling control of a computing system as described herein caninclude determining a number of sensitivity functions for a numbercontrol loops of a cooling system, determining a number of real-timeperformance metrics for the number of control loops, defining a numberof policies for each of the number of control loops based on the numberof sensitivity functions, and altering a number of set-points for thenumber of control loops based on the number of policies and in responseto the number of real-time performance metrics. In some examples, thenumber of set-points can be altered individually. That is, an absolutevalue of a particular set-point can be altered.

The number of policies can define set-point alterations that canincrease an energy efficiency of the entire cooling system. In someexamples, determining the number of sensitivity functions includescomparing a number of efficiency tradeoffs between a number of set-pointalterations for the number of control loops. As used herein, the numberof sensitivity functions include efficiency tradeoffs and/or correlationfactors between set-points of cooling system controllers. Thecorrelation factors can include a value that represents how changes toan input of the cooling system (e.g., set-point changes, etc.) canaffect changes to an output of the cooling system (e.g., real-timeperformance metrics, etc.). The correlation factors and/or sensitivityfunctions can be utilized to optimize energy utilization of the coolingsystem.

FIGS. 1 and 2 illustrate examples of system 100 and computing device 214consistent with the present disclosure. FIG. 1 illustrates a diagram ofan example of a system 100 for hybrid cooling control of a computingsystem consistent with the present disclosure. The system 100 caninclude a database 104, a hybrid cooling control system 102, and/or anumber of engines (e.g., coordinated controller engine 106, etc.). Thehybrid cooling control system 102 can be in communication with thedatabase 104 via a communication link, and can include the number ofengines (e.g., coordinated controller engine 106, etc.). The hybridcooling control system 102 can include additional or fewer engines thatare illustrated to perform the various functions as will be described infurther detail in connection with FIGS. 3-6.

The number of engines (e.g., coordinated controller engine 106, etc.)can include a combination of hardware and programming, but at leasthardware, that is configured to perform functions described herein(e.g., determine a number of liquid loop set-points and a number of airloop set-points, determine a number of system parameters (e.g., fanspeed, pump speed, actuator position, inlet air temperature, real-timeperformance metrics, etc.) corresponding to the number of liquid loopset-points and the number of air loop set-points, determine acorrelation factor for the number of system parameters, alter the numberof liquid loop set-points and the number of air loop set-points based onthe correlation factor to lower an energy consumption or to maximizeenergy reuse of a number of cooling resources associated with the numberof system parameters, etc.). The programming can include programinstructions (e.g., software, firmware, etc.) stored in a memoryresource (e.g., computer readable medium, machine readable medium, etc.)as well as hard-wired program (e.g., logic).

The coordinated controller engine 106 can include hardware and/or acombination of hardware and programming, but at least hardware, todetermine a number of liquid loop set-points and a number of air loopset-points. The number of liquid loop set-points can be system parametersettings corresponding to a liquid cooling system. For example, thesystem parameter settings of the liquid cooling system can include pumpspeed, pump pressure, inlet liquid temperature, component return watertemperature (e.g., outlet liquid temperature), among other settings of aliquid cooling system that can be adjusted. The number of air loopset-points can be system parameter settings corresponding to an aircooling system. For example, the system parameter settings correspondingto the air cooling system can include fan speed, air inlet temperature,and/or air outlet temperature, among other settings of an air coolingsystem that can be adjusted. In some examples, the controllers may notbe able to tune or alter the temperatures of their corresponding controlloops, but instead utilize a number of actuators to alter coolingresources (e.g., water or air temperatures, pressures or flow rates,etc.).

The coordinated controller engine 106 can include hardware and/or acombination of hardware and programming, but at least hardware, todetermine a number of system parameters corresponding to the number ofliquid loop set-points and the number of air loop set-points.Determining the number of system parameters can include determiningreal-time performance metrics of the cooling system. For example,determining the number of system parameters can include determining afan speed, determining a pump speed, determining an inlet airtemperature, determining an inlet liquid temperature, determining anoutlet air temperature, determining an component return watertemperature (e.g., outlet liquid temperature), among other real-timeperformance metrics of the cooling system. In some examples, the numberof liquid loop set-points can alter the number of system parameterscorresponding to the air loop set-points. In addition, the number of airloop set-points can alter the number of system parameters correspondingto the liquid loop set-points.

The coordinated controller engine 106 can include hardware and/or acombination of hardware and programming, but at least hardware, todetermine a correlation factor for the number of system parameters. Thecorrelation factor can be a value that represents how a set-point of theliquid loop or air loop affects the performance metrics of the coolingsystem and/or an energy consumption of the cooling system. For example,a set-point of component return water temperature can have a correlationfactor that can indicate increasing the set-point of the componentreturn water temperature can affect with the inlet water temperature.That is, the correlation factor can represent a trade-off between thecomponent return water temperature and the inlet water temperature. Inthis example, the correlation factor can be utilized to optimize energyconsumption of the cooling system. That is, the correlation factor canbe used to determine set-points to adjust that can optimize energyconsumption and increase cooling capacity of the cooling system. In someexamples, the correlation factor for the number of system parametersrepresents an altered energy consumption of a number of coolingresources associated with the number of system parameters for each ofthe number of air loop set-points and the number of liquid loopset-points. The correlation factor can represent an altered energyconsumption of a number of cooling resources associated with the numberof system parameters and an altered cooling capacity utilization of aliquid loop and an air loop.

The coordinated controller engine 106 can include hardware and/or acombination of hardware and programming, but at least hardware, to alterthe number of liquid loop set-points and the number of air loopset-points based on the correlation factor to lower an energyconsumption or to maximize energy reuse of a number of cooling resourcesassociated with the number of system parameters. The coordinatedcontroller engine 106 can alter the number of liquid loop and air loopset-points based on the correlation factors assigned to each of theset-points and the real-time system parameters of the cooling system.That is, the coordinated controller engine 106 can tune a number ofset-points for a number of individual control loops to lower an energyconsumption or to maximize energy reuse of a number of cooling resourcesassociated with the number of system parameters. In some examples, thecoordinated controller engine 106 can tune the number of set-pointscorresponding to a number of individual controllers that can be utilizedto alter a number of actuators to adjust the cooling capacity of acorresponding control loop.

FIG. 2 illustrates a diagram of an example computing device 214consistent with the present disclosure. The computing device 214 canutilize software, hardware, firmware, and/or logic to perform functionsdescribed herein.

The computing device 214 can be any combination of hardware and programinstructions configured to share information. The hardware, for example,can include a processing resource 216 and/or a memory resource 220(e.g., computer-readable medium (CRM), machine readable medium (MRM),database, etc.). A processing resource 216, as used herein, can includeany number of processors capable of executing instructions stored by amemory resource 220. Processing resource 216 may be implemented in asingle device or distributed across multiple devices. The programinstructions (e.g., computer readable instructions (CRI)) can includeinstructions stored on the memory resource 220 and executable by theprocessing resource 216 to implement a desired function (e.g., receivereal-time parameters for an air loop and a liquid loop of a coolingsystem, determine set-points of the cooling system, wherein theset-points include air loop set-points and liquid loop set-points,determine a correlation factor between the set-points of the coolingsystem and the real-time parameters for the air loop and the liquidloop, alter a number of set-points of the cooling system based on thecorrelation factor to increase an efficiency of the cooling system,etc.).

The memory resource 220 can be in communication with a processingresource 216. A memory resource 220, as used herein, can include anynumber of memory components capable of storing instructions that can beexecuted by processing resource 216. Such memory resource 220 can be anon-transitory CRM or MRM. Memory resource 220 may be integrated in asingle device or distributed across multiple devices. Further, memoryresource 220 may be fully or partially integrated in the same device asprocessing resource 216 or it may be separate but accessible to thatdevice and processing resource 216. Thus, it is noted that the computingdevice 214 may be implemented on a participant device, on a serverdevice, on a collection of server devices, and/or a combination of theparticipant device and the server device.

The memory resource 220 can be in communication with the processingresource 216 via a communication link (e.g., a path) 218. Thecommunication link 218 can be local or remote to a machine (e.g., acomputing device) associated with the processing resource 216. Examplesof a local communication link 218 can include an electronic bus internalto a machine (e.g., a computing device) where the memory resource 220 isone of volatile, non-volatile, fixed, and/or removable storage medium incommunication with the processing resource 216 via the electronic bus.

A number of modules (e.g., coordinated controller module 222, etc.) caninclude CRI that when executed by the processing resource 216 canperform functions. The number of modules (e.g., coordinated controllermodule 222, etc.) can be sub-modules of other modules. In anotherexample, the number of modules (e.g., coordinated controller module 222,etc.) can comprise individual modules at separate and distinct locations(e.g., CRM, etc.).

Each of the number of modules (e.g., coordinated controller module 222,etc.) can include instructions that when executed by the processingresource 216 can function as a corresponding engine as described herein.For example, the coordinated controller module 222 can includeinstructions that when executed by the processing resource 216 canfunction as the coordinated controller engine 106.

FIG. 3 illustrates a diagram of an example of a system 330 for hybridcooling control of a computing system consistent with the presentdisclosure. The system 330 can include a number of server racks 336-1,336-2 that can utilize a cooling system. The server racks 336-1, 336-2can include computing hardware cooled by a cooling system. The coolingsystem can include a number of cooling loops (e.g., liquid cooling loop,air cooling loop, etc.).

The system 330 can include a liquid cooling loop that can include anumber of cooling distribution units (CDU) 332-1, 332-2. The number ofCDUs 332-1, 332-2 can provide liquid to cool hardware of the serverracks 336-1, 336-2 via a liquid cooling loop. The number of CDUs 332-1,332-2 can be coupled to a chiller that provides cool liquid to a numberof racks 336-1, 336-2 via a number of liquid pumps and/or liquid lines(e.g., liquid pipes, etc.). The chiller can utilize a heat exchanger(e.g., heat exchanger 334-1, heat exchanger 334-2, etc.) to remove heatfrom the liquid returning from the server racks 336-1, 336-2, and toisolate the IT from what is usually “dirty” facility water.

The number of CDUs 332-1, 332-2 can circulate the liquid via a number ofliquid lines coupled to the server racks 336-1, 336-2. The liquid linescan be coupled to IT water cooling loops (ITWCL) and/or heat exchangerswithin each of the number of server racks 336-1, 336-2. The ITWCLsand/or heat exchangers within the number of server racks 336-1, 336-2can be utilized to maintain a temperature of computing hardware withinthe server racks 336-1, 336-2. That is, the liquid can be utilized toremove heat generated by the computing hardware within the server racks336-1, 336-2.

In some examples, the cooling system can include an air loop. The airloop can include a number of rack fans, heat exchanger fans, and/orserver fans that can be utilized to circulate air within server racks336-1, 336-2. The air loop can be utilized to provide air cooling to theserver racks 336-1, 336-2. The air loop can utilize (e.g., manipulate,etc.) inlet air at a particular temperature and circulate the inlet airthrough the server racks 336-1, 336-2. The inlet air can be utilized toremove heat from the computing hardware within the server racks 336-1,336-2.

The cooling system can utilize a number of set-points to control thenumber of cooling loops (e.g., air loops, liquid loops, etc.). Each ofthe number of cooling loops can have set-points to activate, deactivate,and/or adjust cooling resources (e.g., cooling devices, etc.) as basedon real-time parameter feedback. As described herein, the set-points canbe compared to real-time parameter feedback, and based upon thecomparison, a number of actuator adjustments can be made by acorresponding controller to activate, deactivate, and/or adjust acooling resource corresponding to the set-point. For example, the liquidcooling loop can include a set-point for water temperature. In thisexample, the actual water temperature can be the real-time parameterfeedback. In this example, a set-point for water temperature can be setat a particular temperature and when the water temperature reaches theparticular temperature a chiller can be activated, switched to aparticular operation model, and/or tuned through a number of temperatureset-points to begin cooling the water to a lower temperature than theparticular temperature. In some examples, when the water temperaturereaches the particular temperature a CDU actuator valve 333-1, 333-2 canbe opened to a greater level (e.g., opened more, etc.) to allowadditional facility water flowing through the heat exchangers within theIT racks 336-1, 336-2 and potentially yielding cooler IT water. Theliquid loop and the air loop can include a number of differentset-points that can operate independently based on independent real-timeparameter feedback to control various performance metrics of the coolingsystem.

The system 330 can integrate the number of different set-points andadjust the number of different set-points to optimize energy efficiencyof the cooling system. The system 330 can utilize real-time performancemetrics of the cooling system with a number of correlation factors toadjust set-points of the number of cooling loops. The number ofcorrelation factors can include representative values for each of thenumber of set-points. The representative values can be values thatindicate how an adjustment of a set-point affects performance metrics ofthe cooling system. For example, a set-point for water temperature caninclude a correlation factor that indicates a relationship between aparticular temperature set-point and performance metrics of the coolingsystem. In addition, the set-point for water temperature can be assigneda correlation factor that indicates a relationship between a particulartemperature set-point and energy utilization of the cooling system.

The correlation factors for the set-points can be utilized to generate anumber of profiles for the cooling system. The number of profiles can beutilized to adjust the set-points to optimize the performance metricsand the energy utilization of the cooling system. The system 330 can beutilized to optimize energy efficiency of an overall cooling system byaltering set-points based on the number of profiles.

FIG. 4 illustrates a diagram of an example of a system 440 for hybridcooling control of a computing system consistent with the presentdisclosure. The system 440 can represent a number of controllers (e.g.,air controller 448, server fan controller 450, water controller 452,etc.) that can be utilized to control settings (e.g., set-points,actuator settings, etc.) for a number of cooling loops.

The number of controllers can utilize a number of set-points (e.g.,inlet temperature set-point 442, server component temperature set-point444, component return water temperature set-point 446, etc.) toactivate, deactivate, or adjust settings for cooling loops (e.g., airloop, liquid loop, etc.). For example, the air controller 448 canutilize the inlet temperature set-point 442 to adjust heat exchangerfans and/or rack fans of the server rack 454. A number of monitors canbe utilized to monitor the performance metrics of the server rack 454and provide the number of performance metrics to each of the number ofcontrollers.

In previous cooling systems the controllers can act independently toadjust the settings of the cooling loops. By acting independently basedon the received number of set-points, the number of controllers canadjust set-points of the number of cooling loops without considering howthe adjustments can affect other performance metrics of the coolingsystem. In addition, acting independently based on the received numberof set-points can result in excessive energy consumption by the coolingsystem. In some previous computing systems the set-points of thecontrollers were adjusted manually to adjust the controllersindividually.

The system 440 can determine a number of correlation factors of theset-points for the number of controllers. The number of correlationfactors can be determined based on real-time performance metrics 456-1,456-2, 456-3, 456-4 of the server rack 454 at each of a number ofset-point combinations. For example, an inlet temperature set-point forthe air controller 448 can affect a server air pressure drop 456-2, aserver component temperature 456-3, and/or an component return watertemperature 456-4 of the server rack 454. In this example, an alterationto the inlet temperature set-point can affect the real-time performancemetrics 456-1, 456-2, 456-3, 456-4 of the server rack 454. The effectthat alterations of the inlet temperature set-point have on thereal-time performance metrics 456-1, 456-2, 456-3, 456-4 of the serverrack 454 can be utilized to generate a correlation factor for the inlettemperature set-point. That is, the correlation factor of the inlettemperature set-point can represent how altering the inlet temperatureset-point affects the real-time performance metrics 456-1, 456-2, 456-3,456-4 of the server rack 454. In some examples, the correlation factorof the inlet temperature set-point can also represent changes in energyconsumption of the cooling system.

The correlation factors for each of the set-points corresponding to eachof the controllers can be utilized to generate a number of profiles forthe system 440. The number of profiles can define what controllerset-points are adjusted based on the real-time performance metrics456-1, 456-2, 456-3, 456-4 of the server rack 454 and the correlationfactors for each of the set-points. In some examples, the number ofprofiles can be utilized to increase cooling capacity utilization of thesystem 440 while also optimizing energy consumption of the system 440.

FIG. 5 illustrates a diagram of an example of a system 580 for hybridcooling control of a computing system consistent with the presentdisclosure. The system 580 can represent an example liquid loop of acooling system. The liquid loop can include a water flow controller 566and a water temperature controller 568. The water flow controller 566can be utilized to regulate the liquid flow of a cooling distributionunit (CDU) 570 utilizing a number of set-points 562, 564. The watertemperature controller 568 can be utilized to regulate the liquidtemperature of a CDU 570. The water temperature controller 568 canutilize a number of set-points 564 that can be utilized to activate,deactivate, and/or alter settings of a number of liquid pumps asdescribed herein.

The water flow controller 566 can utilize real-time differentialpressure 572-1 received from a number of monitors within the CDU 570 toactivate, deactivate, and/or alter settings of a number of liquid pumpsof the CDU 570. That is, the water flow controller 566 can have aparticular differential pressure set-point 562 that can be utilized toalter pump speeds based on received real-time differential pressures572-1. In some examples, altering the pump speed based on the receivedreal-time differential pressures 572-1 can also affect other real-timeparameters (e.g., component supply water temperature 572-2, etc.).

The water temperature controller 568 can utilize a temperature set-point564 in a similar manner as the water flow controller 566. That is, thewater temperature controller 568 can receive real-time component supplywater temperatures 572-2 (e.g., component supply water temperatures,etc.) from a number of monitors coupled to the CDU 570 and based on thetemperature set-point 564, the water temperature controller 568 canalter a facility water valve to alter the component supply watertemperature 572-2 of the CDU 570. In some examples, altering thefacility water valve may also affect other real-time parameters of thesystem 580. In some examples, the number of monitors coupled to the CDU570 can be located within an IT rack. In addition, there can be aplurality of monitors located at various areas of the cooling system.The plurality of monitors can provide a number of monitored temperaturevalues among other real-time parameters (e.g., air temperature, watertemperature, component temperature, energy utilization, fan speed, pumpspeed, etc.) that can be monitored. In some examples, the watertemperature controller 568 can utilize at least one of: a maximumreceived value from the number of monitors, a minimum received value, oran average received value (e.g., mean, medium, etc.).

In some examples, the differential pressure set-point 562 and thetemperature set-point 564 can be assigned a correlation factor based onthe received real-time parameters 572-1, 572-2 when alterations to thedifferential pressure set-point 562 and the temperature set-point 564are implemented. The correlation factors can be utilized to generateprofiles for the system 580. The profiles for the system 580 can includethe correlation factors and set-point alterations that can increasecooling efficiency and optimize energy utilization of the system 580.

FIG. 6 illustrates a diagram of an example of a system 680 for hybridcooling control of a computing system consistent with the presentdisclosure. The system 680 can include cooling distribution unit (CDU)and server rack controlled systems 686 to simultaneously control airloops and liquid loops as described herein. The air loops and liquidloops can be simultaneously controlled by a coordinated controller 682.In some examples, the coordinated controller 682 can replace thefunctions of the number of controllers described herein (e.g., aircontroller, server fan controller, water controller, water flowcontroller, water temperature controller, etc.). In some examples, thecoordinated controller 682 can be utilized to manage and/or control oneor more of the number of controllers described herein. That is, thecoordinated controller 682 can send instructions to a number of lowerlevel controllers. In this example, the lower level controllers can makeset-point alterations as described herein in response to the receivedinstructions from the coordinated controller 682.

The coordinated controller 682 can include a plurality of set-points(e.g., change in pressure set-point 684-1, temperature set-point 684-2,component return water temperature set-points 684-3, etc.) correspondingto a number of controllers of the liquid loop and air loop as describedherein. The coordinated controller 682 can utilize the set-points forthe number of controllers to activate, deactivate, and/or alter settingsof cooling equipment associated with the number of controllers. Forexample, the set-points can be utilized to activate, deactivate, and/oralter a fan speed of a rack fan that is associated with a fancontroller.

The coordinated controller 682 can receive a number of real-timeperformance metrics 688-1, 688-2, 688-3, 688-4 of the CDU and serverrack system 686. The real-time performance metrics can include, but arenot limited to: pump speed and pump power 688-1, fan speed and fan power688-2, server component temperatures 688-3, and/or component returnwater temperatures 688-4. The coordinated controller 682 can determine anumber of correlation factors for the number of set-points 684-1, 684-2,684-3. The correlation factors can be assigned to each of the number ofset-points 684-1, 684-2, 684-3. As described herein, the correlationfactors can represent how particular set-points 684-1, 684-2, 684-3 canaffect the real-time performance metrics 688-1, 688-2, 688-3, 688-4 ofthe CDU and server rack system 686. In addition, the correlation factorscan represent how particular set-points 684-1, 684-2, 684-3 can affectthe system's energy consumption or reuse of the energy (e.g., energyreuse, etc.) contained in the exhaust water (e.g., component returnwater, etc.) of the IT racks. In some examples, the pump speed and powermetric 688-1 and/or the fan speed and power metric 688-2 can be used toquantify cooling energy consumption of the cooling system 680.

In some examples, the correlation factors can be assigned to a number ofset-point combinations. For example, a correlation factor can beassigned to a combination of various set-points 684-1, 684-2, 684-3. Inthis example, different combinations of various set-points 684-1, 684-2,684-3 can affect the real-time performance metrics 688-1, 688-2, 688-3,688-4 of the CDU and server rack system 686 as well as affect the energyconsumption of the CDU and server rack system 686. As described herein,the correlation factors can be utilized to generate a number of profilesthat can be utilized by the coordinated controller 682 to adjust thenumber of set-points 684-1, 684-2, 684-3 for optimizing cooling capacityand optimizing energy consumption of the CDU and server rack system 686,or the reuse of the energy contained in the exhaust water of the ITracks (e.g., energy reuse, etc.). Thus, the correlation factor caninclude direct and indirect alteration values for real-time parametersfor the air loop and the liquid loop of the cooling system.

In some examples, the system 680 can operate in a two layer controlfunctionality. That is, there can be a first layer where performancemetrics are controlled through individual control loops of real-timeperformance metrics. The first layer can be similar to operating thenumber of controllers independently based on independent real-timeparameter feedback as described herein. In addition, there can be asecond layer where the control loops of real-time performance metricsare tuned for coordination and energy consumption optimization. Thesecond layer can be utilized to simultaneously control a number ofdifferent cooling loops based on correlation factors to provide highercooling capacity efficiency with higher power and energy consumptionefficiency.

In some examples, the system 680 can utilize correlation factors thatare based on tradeoffs between set-point alterations. In some examples,the tradeoffs can be between performance metrics of different coolingcontrol loops. In some examples, the tradeoffs can be betweenperformance metrics of the same cooling control loop. In addition, thetradeoffs can be between performance metrics of different coolingmethods. For example, the correlation factors can be based in a tradeoffbetween an component supply water temperature and a flow rate. In thisexample, the component supply water temperature can be controlled byaltering a facility water valve and the flow rate can be controlled byaltering a pump speed. In this example, the cooling capacity of thecomponent supply water is proportional to the component supply watertemperature and flow rate of the component supply water. In thisexample, increasing the flow rate or reducing the temperature of thecomponent supply water can both increase the cooling capacity; howeverthe CPU temperature can be more sensitive to the water temperature thanthe flow rate. Thus, in this example, the correlation factor can beutilized to instruct the coordinated controller 682 to lower the watertemperature before increasing the flow rate. In some examples, thecorrelation factor can be utilized to instruct the coordinatedcontroller 682 to decrease the flow rate and/or increase the componentsupply water temperature to maximize the component return temperaturefor energy reuse purposes.

In another example, the tradeoff can be between cooling methods (e.g.,liquid cooling, air cooling, etc.). In this example, the coordinatedcontroller 682 can receive fan speeds from an air cooling method. Inthis example, the fan speed can reach a point that is not at anefficient rate of energy utilization (e.g., greater than 80%, etc.). Inthis example, the coordinated controller 682 can lower the fan speed bylowering an component supply water temperature of a liquid coolingmethod. Thus, in this example, a correlation factor or profile can beutilized to instruct the coordinated controller 682 to utilize a lowerwater temperature to lower fan speed while increasing the energyefficiency of the system 680.

In another example, the tradeoff can be between the component returnwater temperature and an component supply water temperature control ofthe liquid cooling method and/or liquid loop. The correlation among thecomponent return water temperature, flow rate (e.g., pump speed), andthe component supply water temperature can include a correlation factorthat can be utilized to instruct the coordinated controller 682 to tunethe pressure change, inlet water temperature, and/or component supplywater temperature set-points to optimize the overall energy efficiencyof the system 680. In this example, the component return watertemperature and the component supply temperature can affect an optimalpump speed for cooling capacity. Thus, the coordinated controller 682can utilize a correlation factor assigned to combinations of componentsupply water temperature, component return water temperature, and pumpspeed to alter corresponding set-points to increase cooling capacityand/or optimize energy utilization. In some examples, the system 680 canrespond to an overheating of the computing components. In theseexamples, the local and/or lower level controllers can be at a pointwhere they can make a relatively little increase in cooling capacity forthe system 680 (e.g., fans are already at 100% capacity). In theseexamples, the coordinated controller 682 can determine whether to lowerthe water temperature set-point and/or increase a flow rate of thesystem 680.

As used herein, “logic” is an alternative or additional processingresource to perform a particular action and/or function, etc., describedherein, which includes hardware, e.g., various forms of transistorlogic, application specific integrated circuits (ASICs), etc., asopposed to computer executable instructions, e.g., software firmware,etc., stored in memory and executable by a processor. Further, as usedherein, “a” or “a number of” something can refer to one or more suchthings. For example, “a number of widgets” can refer to one or morewidgets.

The above specification, examples and data provide a description of themethod and applications, and use of the system and method of the presentdisclosure. Since many examples can be made without departing from thespirit and scope of the system and method of the present disclosure,this specification merely sets forth some of the many possible exampleconfigurations and implementations.

What is claimed is:
 1. A system for hybrid cooling control of acomputing system, comprising: a coordinated controller engine to:determine a number of liquid loop set-points and a number of air loopset-points; determine a number of system parameters corresponding to thenumber of liquid loop set-points and the number of air loop set-points;determine a correlation factor for the number of system parameters; andalter the number of liquid loop set-points and the number of air loopset-points based on the correlation factor to lower an energyconsumption or to maximize energy reuse of a number of cooling resourcesassociated with the number of system parameters.
 2. The system of claim1, wherein the number of liquid loop set-points alter the number ofsystem parameters corresponding to an air loop and a liquid loop andwherein the number of air loop set-points alter the number of systemparameters corresponding to the air loop and the liquid loop.
 3. Thesystem of claim 1, comprising the coordinated controller engine to alteran absolute value of a particular set-point from the number of air loopset-points or the number of liquid loop set points.
 4. The system ofclaim 1, wherein the correlation factor for the number of systemparameters represents an altered energy consumption of cooling devicesof an air loop and a liquid loop.
 5. The system of claim 1, wherein thecorrelation factor represents an altered energy consumption or energyreuse of a number of cooling resources associated with the number ofsystem parameters and an altered cooling capacity of a liquid loop andan air loop.
 6. The system of claim 1, wherein the number of air loopset-points include set-points that correspond to an air cooling system.7. The system of claim 1, wherein the number of liquid loop set-pointsinclude set-points that correspond to a liquid cooling system.
 8. Anon-transitory computer readable medium storing instructions executableby a processing device for hybrid cooling control of a computing system,wherein the instructions are executable to: receive real-time parametersfor an air loop and a liquid loop of a cooling system; determineset-points of the cooling system, wherein the set-points include airloop set-points and liquid loop set-points; determine a correlationfactor between the set-points of the cooling system and the real-timeparameters for the air loop and the liquid loop; and alter a number ofset-points of the cooling system based on the correlation factor toincrease an efficiency of the cooling system.
 9. The medium of claim 8,wherein the correlation factor is a representative value of coolingefficiency and energy efficiency of the cooling system.
 10. The mediumof claim 8, wherein the instructions to alter the number of set-pointsof the cooling system includes instructions to alter at least one of:water flow rate; supply water temperature; component air flow rate;component inlet air temperature; component return water temperature; andcomponent outlet air temperature.
 11. The medium of claim 8, wherein thecorrelation factor includes direct and indirect alteration values forset-points that correspond to the real-time parameters for the air loopand the liquid loop of the cooling system.
 12. A method for hybridcooling control of a computing system, comprising: determining a numberof sensitivity functions for a number control loops of a cooling system;determining a number of real-time performance metrics for the number ofcontrol loops; defining a number of policies for each of the number ofcontrol loops based on the number of sensitivity functions; and alteringa number of set-points for the number of control loops based on thenumber of policies and in response to the number of real-timeperformance metrics.
 13. The method of claim 12, wherein defining thenumber of policies includes comparing the number of real-timeperformance metrics to an overall performance metric of the coolingsystem.
 14. The method of claim 12, wherein determining the number ofsensitivity functions includes comparing a number of efficiencytradeoffs between a number of set-point alterations for the number ofcontrol loops.
 15. The method of claim 12, wherein defining the numberof policies includes determining a number of possible set-pointalterations for the number of control loops.